Overload List
| # | Signature | Description |
|---|---|---|
| 1 | void InverseGaussianPDF(TDenseMtxVec X, Double Mu, Double Lambda, TDenseMtxVec Res) | Inverse Gaussian distribution PDF (vectorized). |
| 2 | Double InverseGaussianPDF(Double x, Double Mu, Double Lambda) | Inverse Gaussian (Wald) probability density function (PDF). |
Overload 1: void InverseGaussianPDF(TDenseMtxVec X, Double Mu, Double Lambda, TDenseMtxVec Res)
Inverse Gaussian distribution PDF (vectorized).
| # | Name | Description |
|---|---|---|
| 1 | X | Defines distribution domain, vector or matrix with positive real values. |
| 2 | Mu | Defines distribution Mu parameter. Mu must be a positive scalar. |
| 3 | Lambda | Defines distribution Lambda parameter. Lambda must be a positive scalar. |
| 4 | Res | After calculation stores the PDF calculated from X, Mu, and Lambda. Length and Complex properties of Res are adjusted automatically to match Length and Complex properties of X. |
Result: stored in self (calling object)
Overload 2: Double InverseGaussianPDF(Double x, Double Mu, Double Lambda)
Inverse Gaussian (Wald) probability density function (PDF).
| # | Name | Description |
|---|---|---|
| 1 | x | Function domain, positive real value (x>0). |
| 2 | Mu | Distribution mean parameter. Mu must be a positive scalar (Mu>0). |
| 3 | Lambda | Distribution shape parameter. Lambda must be a positive scalar (Lambda>0). |
Returns: Double - the inverse Gaussian PDF for value x using parameters Mu (mean) and Lambda (shape), where both Mu and Lambda are positive. Returns NaN if Mu<=0, Lambda<=0, or x<=0.
Remarks:
Calculates the inverse Gaussian (Wald) probability density function, defined by
PDF(x | mu,lambda) = sqrt(lambda/(2pi x^3)) exp[(-lambda(x-mu)^2)/(2 x mu^2)] , x > 0, mu > 0, lambda > 0 .
Returns NaN for x<=0, Mu<=0 or Lambda<=0.